Biblio
A Mobile ad hoc network (MANET) is a set of nodes that communicate together in a cooperative way using the wireless medium, and without any central administration. Due to its inherent open nature and the lack of infrastructure, security is a complicated issue compared to other networks. That is, these networks are vulnerable to a a wide range of attacks at different network layers. At the network level, malicious nodes can perform several attacks ranging from passive eavesdropping to active interfering. Wormhole is an example of severe attack that has attracted much attention recently. It involves the redirection of traffic between two end-nodes through a Wormhole tunnel, and manipulates the routing algorithm to give illusion that nodes located far from each other are neighbors. To handle with this issue, we propose a novel detection model to allow a node to check whether a presumed shortest path contains a Wormhole tunnel or not. Our approach is based on the fact that the Wormhole tunnel reduces significantly the length of the paths passing through it.
Routing security plays an important role in Mobile Ad hoc Networks (MANETs). Despite many attempts to improve its security, the routing procedure of MANETs remains vulnerable to attacks. Existing approaches offer support for detecting attacks or debugging in different routing phases, but many of them have not considered the privacy of the nodes during the anomalies detection, which depend on the central control program or a third party to supervise the whole network. In this paper, we present an approach called LAD which uses the raw logs of routers to construct control a flow graph and find the existing communication rules in MANETs. With the reasoning rules, LAD can detect both active and passive attacks launched during the routing phase. LAD can also protect the privacy of the nodes in the verification phase with the specific Merkle hash tree. Without deploying any special nodes to assist the verification, LAD can detect multiple malicious nodes by itself. To show that our approach can be used to guarantee the security of the MANETs, we deploy our experiment in NS3 as well as the practical router environment. LAD can improve the accuracy rate from 2.28% to 29.22%. The results show that LAD performs limited time and memory usages, high detection and low false positives.
Mobile ad-hoc network (MANET) is a system of wireless mobile nodes that are dynamically self-organized in arbitrary and temporary topologies, that have received increasing interest due to their potential applicability to numerous applications. The deployment of such networks however poses several security challenging issues, due to their lack of fixed communication infrastructure, centralized administration, nodes mobility and dynamic topological changes, which make it susceptible to passive and active attacks such as single and cooperative black hole, sinkhole and eavesdropping attacks. The mentioned attacks mainly disrupt data routing processes by giving false routing information or stealing secrete information by malicious nodes in MANET. Thus, finding safe routing path by avoiding malicious nodes is a genuine challenge. This paper aims at combining the existing cooperative bait detection scheme which uses the baiting procedure to bait malicious nodes into sending fake route reply and then using a reverse tracing operation to detect the malicious nodes, with an RSA encryption technique to encode data packet before transmitting it to the destination to prevent eavesdropper and other malicious nodes from unauthorized read and write on the data packet. The proposed work out performs the existing Cooperative Bait Detection Scheme (CBDS) in terms of packet delivery ratio, network throughput, end to end delay, and the routing overhead.
Mobile ad hoc networks (MANETs) are a set of mobile wireless nodes that can communicate without the need for an infrastructure. Features of MANETs have made them vulnerable to many security attacks including wormhole attack. In the past few years, different methods have been introduced for detecting, mitigating, and preventing wormhole attacks in MANETs. In this paper, we introduce a new decentralized scheme based on statistical metrics for detecting wormholes that employs “number of new neighbors” along with “number of neighbors” for each node as its parameters. The proposed scheme has considerably low detection delay and does not create any traffic overhead for routing protocols which include neighbor discovery mechanism. Also, it possesses reasonable processing power and memory usage. Our simulation results using NS3 simulator show that the proposed scheme performs well in terms of detection accuracy, false positive rate and mean detection delay.
With the progress over technology, it is becoming viable to set up mobile ad hoc networks for non-military services as like well. Examples consist of networks of cars, law about communication facilities into faraway areas, and exploiting the solidity between urban areas about present nodes such as cellular telephones according to offload or otherwise keep away from using base stations. In such networks, there is no strong motive according to assume as the nodes cooperate. Some nodes may also be disruptive and partial may additionally attempt according to save sources (e.g. battery power, memory, CPU cycles) through “selfish” behavior. The proposed method focuses on the robustness of packet forwarding: keeping the usual packet throughput over a mobile ad hoc network in the rear regarding nodes that misbehave at the routing layer. Proposed system listen at the routing layer or function no longer try after address attacks at lower layers (eg. jamming the network channel) and passive attacks kind of eavesdropping. Moreover such functionate now not bear together with issues kind of node authentication, securing routes, or message encryption. Proposed solution addresses an orthogonal problem the encouragement concerning proper routing participation.
Mobile Ad-Hoc Networks (MANETs) are prone to many security attacks. One such attack is the blackhole attack. This work proposes a simple and effective application layer based intrusion detection scheme in a MANET to detect blackholes. The proposed algorithm utilizes mobile agents (MA) and wtracert (modified version of Traceroute for MANET) to detect multiple black holes in a DSR protocol based MANET. Use of MAs ensure that no modifications need to be carried out in the underlying routing algorithms or other lower layers. Simulation results show successful detection of single and multiple blackhole nodes, using the proposed detection mechanism, across varying mobility speeds of the nodes.
Mobile Ad Hoc Network (MANET) is pretty vulnerable to attacks because of its broad distribution and open nodes. Hence, an effective Intrusion Detection System (IDS) is vital in MANET to deter unwanted malicious attacks. An IDS has been proposed in this paper based on watchdog and pathrater method as well as evaluation of its performance has been presented using Dynamic Source Routing (DSR) and Ad-hoc On-demand Distance Vector (AODV) routing protocols with and without considering the effect of the sinkhole attack. The results obtained justify that the proposed IDS is capable of detecting suspicious activities and identifying the malicious nodes. Moreover, it replaces the fake route with a real one in the routing table in order to mitigate the security risks. The performance appraisal also suggests that the AODV protocol has a capacity of sending more packets than DSR and yields more throughput.
A Mobile ad hoc Network (MANET) is a self-configure, dynamic, and non-fixed infrastructure that consists of many nodes. These nodes communicate with each other without an administrative point. However, due to its nature MANET becomes prone to many attacks such as DoS attacks. DoS attack is a severe as it prevents legitimate users from accessing to their authorised services. Monitoring, Detection, and rehabilitation (MrDR) method is proposed to detect DoS attacks. MrDR method is based on calculating different trust values as nodes can be trusted or not. In this paper, we evaluate the MrDR method which detect DoS attacks in MANET and compare it with existing method Trust Enhanced Anonymous on-demand routing Protocol (TEAP) which is also based on trust concept. We consider two factors to compare the performance of the proposed method to TEAP method: packet delivery ratio and network overhead. The results confirm that the MrDR method performs better in network performance compared to TEAP method.
In Mobile Ad-hoc Network (MANET), we cannot predict the clear picture of the topology of a node because of its varying nature. Without notice participation and departure of nodes results in lack of trust relationship between nodes. In such circumstances, there is no guarantee that path between two nodes would be secure or free of malicious nodes. The presence of single malicious node could lead repeatedly compromised node. After providing security to route and data packets still, there is a need for the implementation of defense mechanism that is intrusion detection system(IDS) against compromised nodes. In this paper, we have implemented IDS, which defend against some routing attacks like the black hole and gray hole successfully. After measuring performance we get marginally increased Packet delivery ratio and Throughput.
For sharing resources using ad hoc communication MANET are quite effective and scalable medium. MANET is a distributed, decentralized, dynamic network with no fixed infrastructure, which are self- organized and self-managed. Achieving high security level is a major challenge in case of MANET. Layered architecture is one of the ways for handling security challenges, which enables collection and analysis of data from different security dimensions. This work proposes a novel multi-layered outlier detection algorithm using hierarchical similarity metric with hierarchical categorized data. Network performance with and without the presence of outlier is evaluated for different quality-of-service parameters like percentage of APDR and AT for small (100 to 200 nodes), medium (200 to 1000 nodes) and large (1000 to 3000 nodes) scale networks. For a network with and without outliers minimum improvements observed are 9.1 % and 0.61 % for APDR and AT respectively while the maximum improvements of 22.1 % and 104.1 %.
Mobile Ad-hoc network is decentralized and composed of various individual devices for communicating with each other. Its distributed nature and infrastructure deficiency are the way for various attacks in the network. On implementing Intrusion detection systems (IDS) in ad-hoc node securities were enhanced by means of auditing and monitoring process. This system is composed with clustering protocols which are highly effective in finding the intrusions with minimal computation cost on power and overhead. The existing protocols were linked with the routes, which are not prominent in detecting intrusions. The poor route structure and route renewal affect the cluster hardly. By which the cluster are unstable and results in maximization processing along with network traffics. Generally, the ad hoc networks are structured with battery and rely on power limitation. It needs an active monitoring node for detecting and responding quickly against the intrusions. It can be attained only if the clusters are strong with extensive sustaining capability. Whenever the cluster changes the routes also change and the prominent processing of achieving intrusion detection will not be possible. This raises the need of enhanced clustering algorithm which solved these drawbacks and ensures the network securities in all manner. We proposed CBIDP (cluster based Intrusion detection planning) an effective clustering algorithm which is ahead of the existing routing protocol. It is persistently irrespective of routes which monitor the intrusion perfectly. This simplified clustering methodology achieves high detecting rates on intrusion with low processing as well as memory overhead. As it is irrespective of the routes, it also overcomes the other drawbacks like traffics, connections and node mobility on the network. The individual nodes in the network are not operative on finding the intrusion or malicious node, it can be achieved by collaborating the clustering with the system.
SYN flood attack is a very serious cause for disturbing the normal traffic in MANET. SYN flood attack takes advantage of the congestion caused by populating a specific route with unwanted traffic that results in the denial of services. In this paper, we proposed an Adaptive Detection Mechanism using Artificial Intelligence technique named as SYN Flood Attack Detection Based on Bayes Estimator (SFADBE) for Mobile ad hoc Network (MANET). In SFADBE, every node will gather the current information of the available channel and the secure and congested free (Best Path) channel for the traffic is selected. Due to constant congestion, the availability of the data path can be the cause of SYN Flood attack. By using this AI technique, we experienced the SYN Flood detection probability more than the others did. Simulation results show that our proposed SFADBE algorithm is low cost and robust as compared to the other existing approaches.
Vehicular Adhoc Network (VANET), a specialized form of MANET in which safety is the major concern as critical information related to driver's safety and assistance need to be disseminated between the vehicle nodes. The security of the nodes can be increased, if the network availability is increased. The availability of the network is decreased, if there is Denial of Service Attacks (DoS) in the network. In this paper, a packet detection algorithm for the prevention of DoS attacks is proposed. This algorithm will be able to detect the multiple malicious nodes in the network which are sending irrelevant packets to jam the network and that will eventually stop the network to send the safety messages. The proposed algorithm was simulated in NS-2 and the quantitative values of packet delivery ratio, packet loss ratio, network throughput proves that the proposed algorithm enhance the security of the network by detecting the DoS attack well in time.
For the security of mobile ad-hoc networks (MANETs), a group of wireless mobile nodes needs to cooperate by forwarding packets, to implement an intrusion detection system (IDS). Some of the current IDS implementations in a clustered MANET have designed mobile nodes to wait until the cluster head is elected before scanning the network and thus nodes may be, unfortunately, exposed to several control packet attacks by which nodes identify falsified routes to reach other nodes. In order to detect control packet attacks such as route falsification, we design a route cache sharing mechanism for a non-clustered network where all one-hop routing data are collected by each node for a cooperative host-based detection. The cooperative host-based detection system uses a Support Vector Machine classifier and achieves a detection rate of around 95%. By successfully detecting the route falsification attacks, nodes are given the capability to avoid other attacks such as black-hole and gray-hole, which are in many cases a result of a successful route falsification attack.
This research proposes an inspection on Trust Based Routing protocols to protect Internet of Things directing to authorize dependability and privacy amid to direction-finding procedure in inaccessible systems. There are number of Internet of Things (IOT) gadgets are interrelated all inclusive, the main issue is the means by which to protect the routing of information in the important systems from different types of stabbings. Clients won't feel secure on the off chance that they know their private evidence could without much of a stretch be gotten to and traded off by unapproved people or machines over the system. Trust is an imperative part of Internet of Things (IOT). It empowers elements to adapt to vulnerability and roughness caused by the through and through freedom of other devices. In Mobile Ad-hoc Network (MANET) host moves frequently in any bearing, so that the topology of the network also changes frequently. No specific algorithm is used for routing the packets. Packets/data must be routed by intermediate nodes. It is procumbent to different occurrences ease. There are various approaches to compute trust for a node such as fuzzy trust approach, trust administration approach, hybrid approach, etc. Adaptive Information Dissemination (AID) is a mechanism which ensures the packets in a specific transmission and it analysis of is there any attacks by hackers.It encompasses of ensuring the packet count and route detection between source and destination with trusted path.Trust estimation dependent on the specific condition or setting of a hub, by sharing the setting information onto alternate hubs in the framework would give a superior answer for this issue.Here we present a survey on various trust organization approaches in MANETs. We bring out instantaneous of these approaches for establishing trust of the partaking hubs in a dynamic and unverifiable MANET atmosphere.
Mobile Ad-hoc Network (MANET) consists of different configurations, where it deals with the dynamic nature of its creation and also it is a self-configurable type of a network. The primary task in this type of networks is to develop a mechanism for routing that gives a high QoS parameter because of the nature of ad-hoc network. The Ad-hoc-on-Demand Distance Vector (AODV) used here is the on-demand routing mechanism for the computation of the trust. The proposed approach uses the Artificial neural network (ANN) and the Support Vector Machine (SVM) for the discovery of the black hole attacks in the network. The results are carried out between the black hole AODV and the security mechanism provided by us as the Secure AODV (SAODV). The results were tested on different number of nodes, at last, it has been experimented for 100 nodes which provide an improvement in energy consumption of 54.72%, the throughput is 88.68kbps, packet delivery ratio is 92.91% and the E to E delay is of about 37.27ms.